Articles | Volume 30, issue 4
Research article
10 Oct 2023
Research article |  | 10 Oct 2023

The joint application of a metaheuristic algorithm and a Bayesian statistics approach for uncertainty and stability assessment of nonlinear magnetotelluric data

Mukesh, Kuldeep Sarkar, and Upendra K. Singh


Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on npg-2023-8', Anonymous Referee #1, 12 May 2023
    • AC1: 'Reply on RC1', Mukesh Mukesh, 12 May 2023
  • RC2: 'Comment on npg-2023-8', Anonymous Referee #2, 04 Jul 2023
    • AC2: 'Reply on RC2', Mukesh Mukesh, 22 Jul 2023

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Mukesh Mukesh on behalf of the Authors (11 Aug 2023)  Author's response   Author's tracked changes   Manuscript 
ED: Publish as is (04 Sep 2023) by Norbert Marwan
AR by Mukesh Mukesh on behalf of the Authors (04 Sep 2023)
Short summary
A hybrid weighted particle swarm optimization (wPSO) and gravitational search algorithm (GSA) is compared with individual PSO and GSA methods to assess 1-D resistivity models from magnetotelluric data across diverse geological terrains. This involved creating numerous models to match apparent resistivity and phase curves, selecting the best-fit models, and conducting posterior PDF, correlation matrix, and stability analysis to improve the mean model's accuracy with minimized uncertainty.